Digital Twins for Decision Intelligence in Complex and Adaptive Systems

Dear Colleagues,

Modern engineered, organizational, and socio-technical systems are becoming increasingly complex, dynamic, and interconnected, creating significant challenges for effective decision-making. Decision Support Systems (DSS) must now operate across multiple temporal and spatial scales while accounting for uncertainty, nonlinearity, and human–system interaction. In this context, Digital Twin (DT) technology has emerged as a powerful systems-oriented paradigm for enhancing decision intelligence.

As dynamic, data-informed virtual counterparts of physical or abstract systems, Digital Twins enable continuous monitoring, simulation, prediction, and control. When embedded within DSS frameworks, they provide a systemic foundation for what-if analysis, scenario evaluation, predictive and prescriptive decision-making, and adaptive system management. Their ability to integrate real-time data, system models, and analytics aligns strongly with the systems thinking and engineering principles emphasized by Systems. Despite rapid growth in DT research, existing studies often remain application-specific or technology-driven, with limited attention to decision processes, system-level integration, and governance across multiple decision layers.

This Special Issue seeks original research and review articles that explore the design, modeling, integration, and application of Digital Twins as decision support mechanisms across strategic, tactical, and operational levels. Emphasis is placed on system architectures, hybrid modeling approaches, real-time analytics, and human–system interaction that enhance decision quality, robustness, and transparency.

Contributions may address theoretical foundations, methodological frameworks, computational techniques, or empirical applications, provided they offer clear system-level insights into decision processes. Interdisciplinary studies that integrate systems thinking, artificial intelligence, simulation, optimization, and data analytics are particularly encouraged. 

Topics of interest include (but are not limited to):

• Systems-based architectures for Digital Twin-enabled DSS;
• Digital Twins for complex, adaptive, and cyber–physical systems;
• Digital Twins for sustainable and resilient systems;
• Model-based, data-driven, and hybrid Digital Twin approaches;
• Systems modeling, simulation, and optimization for decision support;
• Artificial Intelligence and machine learning integration in Digital Twin DSS;
• Human–system interaction and explainable decision support;
• Socio-technical and human-centered Digital Twin design;
• Digital Twins for decision-making in coastal and blue tourism;
• Uncertainty, robustness, and resilience in Digital Twin-based decisions;
• Validation and verification of Digital Twin systems;
• Multi-level decision support (strategic, tactical, operational);
• Applications in engineering systems, smart cities, sustainable destination management, blue economy, education, healthcare, energy, manufacturing, and supply chains.

This Special Issue directly aligns with the scope of Systems by addressing Digital Twin-based Decision Support Systems as complex, integrated systems grounded in systems science and engineering. Digital Twins operationalize core systems concepts—such as feedback loops, system dynamics, multi-level interactions, and emergence—by coupling real-world systems with dynamic virtual models for decision-making.

The topic emphasizes holistic system modeling, simulation, and optimization to support decisions in complex and adaptive environments, which are central themes of Systems. By integrating cyber–physical systems, data-driven and model-based approaches, artificial intelligence, and human-in-the-loop decision processes, the Special Issue reflects the journal’s interdisciplinary focus.

Overall, this Special Issue contributes system-level theories, methods, and applications that advance understandings of how complex systems are analyzed, managed, and governed through decision support, firmly positioning it within the core scope of Systems.

Prof. Dr. Adriana Reveiu
Dr. Lili Zheng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• digital twin
• decision support systems
• intelligent systems
• simulation and optimization
• hybrid modeling
• artificial intelligence
• machine learning
• human-in-the-loop systems
• user experience
• environmental and sustainable decision-making
• sustainable tourism
• coastal systems
• predictive and prescriptive analytics
• system architecture
• uncertainty and resilience
• hybrid modeling (model-based and data-driven)